Search Results (314)

Background/Objectives: Duodenal epithelial neoplasms are rare; however, the widespread use of surveillance endoscopy and advances in endoscopic imaging technology have increased their incidental detection. Owing to their rarity, the clinicopathological characteristics and natural course of duodenal epithelial neoplasms have not been thoroughly investigated. In this study, we aimed to clarify the genomic profile and clinicopathological characteristics of duodenal epithelial neoplasms. Methods: A total of 158 patients with duodenal epithelial neoplasms were enrolled. Comprehensive genomic profiling and immunohistochemical staining were performed. Immunophenotypes were categorized as gastric type (G-type), gastrointestinal type (GI-type), or intestinal type (I-type). The detection rate of potentially actionable genomic alterations and a high tumor mutational burden (TMB-H ≥ 10 Muts/Mb) were evaluated and compared across tumor types. Results: The median size of adenocarcinomas was larger than that of adenomas (p = 0.002). The age at diagnosis of G-type tumors was higher than that for the other two tumor types (p < 0.001). The median size of I-type tumors was smaller than that of the other two tumor types (p = 0.019). Compared with the other two types, G-type tumors were predominantly located in the superior region (p < 0.001), were macroscopic Type I (p = 0.002), and had significantly higher genomic alteration rates for KRAS (p < 0.001), GNAS (p < 0.001), CDKN2A (p = 0.004), and MDM2 (p < 0.001). Eighteen patients showed TMB-H. Conclusions: TMB-H was observed in >10% duodenal tumors. Additionally, the pathogenesis of G-type duodenal tumors differs from that of other immunophenotypic tumors. These findings could help in understanding the genomic profiles of duodenal tumors and in selecting treatment options. Full article

Background: Comprehensive genomic profiling (CGP) via next-generation sequencing (NGS) is pivotal for precision oncology, yet many laboratories face challenges with incomplete genomic coverage, complex bioinformatics workflows, and limited integration of key biomarkers. Methods: We evaluated the analytical performance and clinical utility of a CGP assay using 119 tumor samples representing 18 types of cancer, previously analyzed with an orthogonal NGS panel. Concordance was assessed across 81 genes, covering 176 single-nucleotide variants (SNVs), eight copy number variations (CNVs), four deletions, one duplication, and four gene fusions. Limit of detection (LOD) studies employed AcroMetrix Mutant Hotspot Control and SeraSeq Lung and Brain CNV Mix. Microsatellite instability (MSI) and tumor mutational burden (TMB) were quantified. Inter- and intra-run reproducibility were evaluated to assess precision. Results: The CGP assay demonstrated high analytical performance, with >99% sensitivity, 100% specificity, and complete accuracy for variant detection. LOD studies revealed robust detection of SNVs at ≤5% variant allele frequencies (VAF) and CNVs at three copies. MSI and TMB results were consistent with clinical expectations, showing minimal bias compared to the orthogonal panel. Inter- and intra-run testing confirmed 100% reproducibility, indicating strong assay precision. Post-sequencing variant reporting was streamlined using the iCare platform, enabling direct FASTQ-to-report generation without intermediate bioinformatic steps. Conclusions: These findings support the present assay’s clinical utility in personalized oncology assessment. Full article

Non-small cell lung cancer (NSCLC) exhibits genomic heterogeneity that affects tumor immunogenicity and PD-L1 expression. Patient clustering based on shared mutational profiles using social network analysis (SNA) has been narrowly explored. The study aimed to identify subgroups of NSCLC patients with similar somatic mutation profiles using network-based modularity clustering, and to compare these groups with respect to PD-L1 expression, Tumor mutation burden (TMB), and clinical variables. Data of patients with stage 4 (metastatic) NSCLC, whose tumor tissue samples were collected between 2022 and 2024, were analyzed. This retrospective study included NSCLC patients harboring actionable driver mutations in genes such as EGFR, KRAS, ALK, BRAF, MET. A social network of 129 patients was constructed. Two distinct genomic clusters were identified. Cluster 2 (n = 55) showed a higher prevalence of KRAS, TP53, BRAF, STK11 and additional mutations, while cluster 1 (n = 74) displayed a limited number of driver mutations. Cluster 2 had significantly higher PD-L1 expression (29.8% vs. 13.7%, p = 0.001) and higher TMB (7.8 vs. 5.8, p = 0.021). In multivariate logistic regression, both PD-L1 and TMB were associated with cluster assignment (p < 0.05). Mutation-based SNA clustering delineated two biologically distinct subgroups of NSCLC patients. The highly mutated cluster displayed higher PD-L1 expression and TMB, a profile consistent with a more immunogenic phenotype. This method offers a novel integrative approach that requires prospective validation before clinical implementation. Full article

Introduction: Lung cancer, the leading cause of cancer-related mortality worldwide, is a heterogeneous malignancy comprising distinct histological and molecular subtypes, with non-small cell lung cancer (NSCLC) accounting for approximately 85% of cases and adenocarcinoma (ADC) representing the most prevalent histotype. An emerging pathological feature of NSCLC, spread through air spaces (STAS)—defined as the extension of tumor cells into the lung parenchyma beyond the main tumor margin—has been associated with worse disease-free and overall survival and has been proposed as a possible predictor of recurrence to guide surgical extent. Concurrently, recent comprehensive genomic profiling of early-stage NSCLC has highlighted the need to interpret multi-omics data and their relationship with pathological variables, including IASLC histological subtypes, to better personalize treatment strategies. In this context, we investigated the overall distribution of STAS and its association with tumor mutational profiles and IASLC histological subtypes in a large real-world cohort of lung adenocarcinoma patients from the LANTERN project. Materials and Methods: In a prospective, multicenter observational study (March 2023–December 2024), 271 NSCLC patients were enrolled, and clinicopathological, immunohistochemical, and genomic data were collected; comprehensive genomic profiling was performed using the TruSight Oncology 500 assay to analyze 523 cancer-related genes, tumor mutational burden (TMB), and microsatellite instability; and STAS was assessed according to IASLC criteria. Adenocarcinoma accounted for roughly 90% of the cases, with a median age of 69 years and a predominance of stage IV disease (49.5%). STAS was evaluable in 162 cases and was detected in 17.9% of tumors. Results: STAS-positive tumors showed a higher trend towards locally advanced and advanced disease; no differences were observed in sex, age, smoking status, tumor mutational burden, or PD-L1 expression. Additionally, STAS-positive tumors showed a higher association with micropapillary, mucinous, and papillary patterns, whereas the acinar pattern was more frequent in STAS-negative tumors. The most frequently mutated genes were TP53, KRAS, EGFR, and STK11, with no significant differences between groups; ROS1 alterations were absent in STAS-negative tumors but detected more frequently in STAS-positive cases. Conclusions: Overall, these findings indicate that STAS positivity is associated with high-risk histological subtypes and advanced disease, suggesting its importance as a marker of tumor aggressiveness and emphasizing the need for its systematic evaluation in lung adenocarcinoma to better guide surgical planning and patient risk assessment. Full article

The therapeutic armamentarium for colorectal cancer (CRC) has been significantly expanded with the introduction of immunotherapy, particularly immune checkpoint inhibitors (ICIs). However, the response to immunotherapy is strongly dependent on microsatellite instability (MSI) status. Tumors with high MSI (MSI-H) and/or mismatch repair deficiency (dMMR) exhibit high tumor mutational burden (TMB), increased neoantigen load, and enhanced immunogenicity, leading to improved responses to ICIs compared with microsatellite-stable (MSS) and/or mismatch repair-proficient (pMMR) tumors. This has changed the treatment landscape of this small subgroup of metastatic CRC (mCRC), including the approval of pembrolizumab as a first-line option. In contrast, most mCRC cases are MSS/pMMR and are resistant or poorly responsive to ICIs, with no established standard immunotherapy strategy. Therefore, current approaches aim to convert these “cold” tumors into “hot,” immunologically active tumors. This review summarizes the distinct molecular basis of MSI phenotypes and their interaction with the tumor microenvironment, and provides relevant insights into current clinical evidence for prognostic and predictive biomarkers beyond MSI status, as well as novel therapeutic strategies to overcome resistance in MSS disease. Full article

Background: Muscle-invasive bladder cancer (MIBC) is an aggressive disease with heterogeneous responses to neoadjuvant chemotherapy and emerging chemo-immunotherapy combinations. Reliable biomarkers to predict treatment responsiveness before therapy initiation are needed to guide patient selection. Objective: The objective of this study was to identify genomic and immune-related features associated with immune-active tumor phenotypes in MIBC using The Cancer Genome Atlas bladder cancer cohort (TCGA-BLCA). Methods: A retrospective bioinformatics analysis of TCGA-BLCA data was performed, evaluating gene expression, somatic mutations, tumor mutational burden (TMB), DNA damage response (DDR) gene status, and immune infiltration signatures. Immune enrichment metrics were derived from transcriptomic data. In the absence of direct treatment response data, a surrogate immune response classification was applied. Associations were analyzed using descriptive statistics and Firth’s penalized logistic regression. Results: Tumors classified as immune-high phenotype group based on immune-related features exhibited significantly higher global immune infiltration, including increased ImmuneScore and enrichment of cytotoxic and innate immune cells. In multivariable analysis, ImmuneScore was the only independent predictor of inferred responsiveness (p = 0.003). Conclusions: Global immune infiltration showed the strongest association with immune-active tumor phenotypes among the features examined in this TCGA-based analysis. These exploratory findings suggest that immune profiling may warrant further investigation as a component of tumor characterization in MIBC, pending validation in cohorts with clinical treatment and outcome data. Full article

Background: While Immune Checkpoint Inhibitors (ICIs) have significantly improved outcomes in lung cancer (LC), clinical responses remain heterogeneous. Static tissue biomarkers, like PD-L1, and tumor mutational burden (TMB) are limited by intratumoral heterogeneity and the inability to track temporal changes. This review aims to evaluate the current state and future potential of liquid biopsy as a dynamic tool for patient selection, treatment monitoring, and the identification of resistance mechanisms in LC immunotherapy. Methods: A literature search was conducted in the PubMed database up to March 2026. We identified 65 eligible publications, including clinical trials, observational studies, and systematic reviews, focusing on liquid biopsy analytes such as circulating tumor DNA (ctDNA), circulating tumor cells (CTCs), exosomes, and soluble immune mediators. Results: Liquid biopsy provides a “pooled” representation of the total tumor burden, overcoming the spatial limitations of tissue biopsy. Key findings include that dynamic changes in ctDNA and bTMB can predict molecular progression weeks before radiological assessment; blood-based PD-L1 monitoring (soluble, exosomal, or on CTCs) correlates with survival outcomes and offers a real-time readout of immune checkpoint activity; novel markers like tumor-macrophage fusion (TMF) cells and cytokine signatures provide unique insights into the systemic immune microenvironment. Conclusions: Liquid biopsy is evolving from a complementary diagnostic tool into a central pillar of precision immuno-oncology. Although technical standardization remains a challenge, the integration of multi-omic blood-based biomarkers represents the future of personalized lung cancer management. Full article

Immune checkpoint receptors (ICRs) play a pivotal role in modulating antitumor immunity and have become central targets in the immunotherapy of genitourinary (GU) malignancies. This review provides a comprehensive overview of the fundamental mechanisms of ICR signaling, the expression and pathophysiological roles of these receptors in GU cancers (kidney, bladder, prostate, testicular, and penile), and the evolving therapeutic landscape. Key ICRs, including PD-1, CTLA-4, LAG-3, TIM-3, and TIGIT, orchestrate complex signaling cascades that can lead to T-cell exhaustion and tumor immune evasion. Their expression varies significantly across GU cancer types, histological subtypes, and tumor stages, influencing prognosis and therapeutic response. Immune checkpoint inhibitors (ICIs) reinvigorate antitumor immunity by disrupting these inhibitory pathways and remodeling the tumor microenvironment (TME); however, resistance mechanisms (primary, adaptive, and acquired) and immune-related adverse events (irAEs) pose significant clinical challenges. Established biomarkers such as PD-L1 expression, tumor mutational burden (TMB), and microsatellite instability (MSI)/deficient mismatch repair (dMMR) status guide ICI use, but their predictive power has limitations. Consequently, emerging tissue-based (e.g., immune cell signatures, multiplex IHC/IF, spatial transcriptomics), liquid biopsy-based (e.g., ctDNA, CTCs, exosomes), and imaging-based (radiomics, AI-driven analysis) biomarkers are under active investigation to refine patient selection and monitor treatment efficacy. The therapeutic armamentarium is rapidly expanding with novel ICIs targeting new receptors, bispecific antibodies, and innovative combination strategies involving ICIs with chemotherapy, targeted therapies, radiotherapy, and other immunotherapies. Furthermore, ICIs are increasingly explored in neoadjuvant, adjuvant, and maintenance settings. This review highlights the dynamic progress in understanding ICR biology and its clinical translation, emphasizing the ongoing efforts to develop more personalized and effective immunotherapeutic strategies for patients with genitourinary tumors. Full article

Background: Endometrial carcinoma (EC) is now classified primarily by molecular subtype—POLE-ultramutated, mismatch repair–deficient (dMMR), TP53-mutant/copy-number-high (CNH), and “no specific molecular profile” (NSMP)—a framework that has reshaped prognostic counseling and adjuvant therapy decisions. Yet several practically important questions remain insufficiently addressed in real-world cohorts: whether all four mismatch repair genes confer an equivalent favorable prognosis, whether all POLE alterations carry the same survival benefit or only specific pathogenic variants, and whether molecular subtypes retain prognostic value after adjustment for histology and tumor burden. Methods: We addressed these questions in 2901 patients pooled from the MSK-IMPACT 50K Clinical Sequencing Cohort (n = 2372; discovery) and the TCGA UCEC PanCancer Atlas (n = 529; validation)—the largest dual-cohort genomic analysis of EC reported to date. We performed individual MMR gene and combined dMMR survival stratification, multivariable Cox regression adjusted for age, histology, and sample type, and a pathogenicity-aware sensitivity analysis for POLE variants, with tumor mutational burden (TMB) compared across subgroups. Results: Across both cohorts, all four MMR gene–mutant subgroups (MLH1, MSH2, MSH6, PMS2) conferred equivalently favorable overall survival (OS) (six-group log-rank p = 7.66 × 10⁻¹² in discovery; p = 6.78 × 10⁻³ in validation), confirming dMMR as a class-level prognostic designation independent of which MMR gene is altered. Multivariable Cox regression demonstrated that POLE-ultramutated status retained an independent favorable effect (HR = 0.62, p = 0.038 in MSK; HR = 0.35, p = 0.028 in TCGA) after adjustment for age, histology, and sample type, while the favorable dMMR effect was largely accounted for by histologic context. Critically, a pathogenicity-aware sensitivity analysis revealed that the exceptional survival of the POLE subgroup is confined to canonical exonuclease-domain hotspot mutations (event rate 0.9% in MSK), whereas POLE variants of uncertain significance behave indistinguishably from NSMP-like tumors. Consistent with this finding, TMB was markedly elevated in canonical pathogenic POLE cases (median 138.7 mut/Mb in MSK; 247.4 in TCGA) but not in POLE-VUS-only cases (median 29.0 and 15.0, respectively; p < 0.001 between groups in both cohorts), confirming that the ultramutator phenotype is confined to canonical pathogenic POLE variants. We additionally characterize Uterine Clear Cell Carcinoma as a distinct histologic entity (n = 73; 3.0%) and report the POLE + TP53 co-mutant group (n = 90; 3.8%). Conclusions: These findings refine the molecular classification of EC in clinically meaningful ways: they support class-level immunotherapy eligibility based on dMMR status regardless of the specific MMR gene altered, demonstrate that POLE-ultramutated classification requires variant-level pathogenicity assessment, and identify TP53-mutant/CNH patients as the population with the most urgent unmet therapeutic need. Full article

Treatment-refractory rectal cancer liver metastasis represents a major therapeutic challenge, particularly in the absence of actionable genomic biomarkers. Functional precision oncology approaches integrating genomic profiling with patient-derived organoid (PDO) drug testing may provide biologically informed therapeutic prioritization. A 50-year-old female patient with KRAS/TP53-mutant, microsatellite-stable (MSS) rectal adenocarcinoma refractory to FOLFIRINOX was enrolled. A liver metastasis from a treatment-refractory rectal cancer patient was processed to establish three-dimensional patient-derived organoids. Histopathological concordance was assessed using H&E and p53 immunohistochemistry. Comprehensive genomic profiling was performed using a 637-gene targeted next-generation sequencing panel, enabling detection of single-nucleotide variants, indels, copy number variations, microsatellite instability, and tumor mutational burden. Functional drug sensitivity profiling was conducted in parallel 2D and 3D platforms using a customized 17-agent panel, followed by exploratory combinatorial validation. The organoids demonstrated high phenotypic and genomic concordance with the parental tumor, preserving key driver alterations (KRAS^A146T, TP53^R175H, APC frameshifts, CCNE1 amplification), microsatellite stability, and low tumor mutational burden (TMB: 6.37 mut/Mb). Functional screening identified selective sensitivity to bevacizumab (IC₅₀: 0.130 μM), doxorubicin (IC₅₀: 0.570 μM), carboplatin (IC₅₀: 0.950 μM), and topotecan (IC₅₀: 1.600 μM) in the 3D organoid model, with consistent cross-platform validation. An exploratory combination assay further supported enhanced viability suppression under bevacizumab-based regimens. Critically, at the time of manuscript preparation, the patient demonstrated radiological disease stabilization under bevacizumab plus trastuzumab deruxtecan, consistent with the organoid-derived response profile. These findings highlight the capacity of integrated genomic and organoid-based profiling to uncover therapeutic vulnerabilities beyond standard biomarker assessment. This proof-of-concept case report study demonstrates the feasibility and translational relevance of an established organoid-based functional precision oncology platform for therapeutic prioritization in metastatic rectal cancer. Full article

Tumor-agnostic therapies represent an evolving approach in oncology, shifting from conventional histology-based treatment models to strategies guided by molecular alterations. Regulatory approvals of therapies targeting tumors harboring genomic alterations such as NTRK and RET fusions, BRAF V600E mutation, and those with deficient mismatch repair (dMMR) and a high tumor mutational burden (TMB-H) have demonstrated clinical activity across multiple cancer types. However, responses to these therapies are not uniform across all tumors. This review examines the variability of clinical outcomes across different cancer histologies and the challenges associated with this tumor-agnostic treatment paradigm. Despite sharing the same molecular alterations, some malignancies, including pancreatic and colorectal cancers, demonstrate lower response rates due to tissue-specific resistance mechanisms such as bypass signaling pathways and co-occurring genomic alterations. We discuss how these biological differences influence treatment response and their implications for future drug development and clinical trial design. Addressing these biological and clinical complexities will be essential to optimize the use of tumor-agnostic therapies across diverse cancer types. Full article

Glioma prognosis is shaped by molecular markers such as IDH mutation, WHO grade, and MGMT methylation, yet heterogeneity persists within defined subgroups. Sidekick Cell Adhesion Molecule 1 (SDK1), an immunoglobulin superfamily member mediating homophilic adhesion, has been documented in glioma tissue but lacks systematic prognostic evaluation. I assessed SDK1’s prognostic value using the Chinese Glioma Genome Atlas (CGGA, N = 503) and The Cancer Genome Atlas (TCGA, N = 572) through multivariate Cox regression, subgroup analyses, differential gene expression, pathway enrichment, ssGSEA-based immune profiling, and molecular subtype association. High SDK1 expression was independently associated with poor overall survival in both cohorts (CGGA: adjusted HR = 1.48, 95% CI 1.16–1.89, p = 0.002; TCGA: HR = 1.76, 95% CI 1.19–2.61, p = 0.005; pooled HR = 1.55, I² = 0%). Effect estimates varied across subgroups, with significant associations in WHO grade IV and IDH-wildtype strata but not in grade II or older patients. Cross-validated differentially expressed genes were enriched in extracellular matrix organization and focal adhesion pathways. Notably, SDK1 expression showed weak but statistically significant correlations with COL1A1-associated mesenchymal program scores (CGGA: R = 0.12, p = 0.008; TCGA: R = 0.15, p < 0.001) and oncostream-related gene signatures (CGGA: R = 0.16, p < 0.001; TCGA: R = 0.086, p = 0.039), suggesting a modest association with mesenchymal invasion programs. SDK1-high tumors showed elevated M2 macrophage and Treg signatures with upregulated immune checkpoints, though cohort-dependent differences were observed. Multivariate Cox analysis demonstrated that the prognostic significance of SDK1 is independent of tumor mutational burden (TMB), with no significant correlation or interaction observed between them (p > 0.05). SDK1 is a candidate prognostic biomarker in glioma co-occurring with ECM remodeling and immunosuppressive features, warranting experimental validation for clinical translation. Full article

Background/Objectives: Overexpression of transferrin receptor (TFR1) is common in cancer and may be associated with inferior treatment outcomes. Due to these patterns and TFR1’s essential role in iron metabolism, the protein has been targeted for cytotoxic drug delivery. More recently, increased TFR1 expression has been linked to tumor microenvironment (TME) infiltration by immune effectors in selected tumors, but a comprehensive assessment of the genomic landscape associated TFRC (the gene encoding TFR1) expression has not been conducted. Methods: By utilizing a pan-cancer database of 93,248 patients with whole-exome and whole-transcriptome sequencing, we assessed TFRC-associated multiomic patterns. Results: We found that high TFRC expression correlates with significantly worse overall survival in multiple common solid tumor types, a higher tumor mutational burden (TMB), an increase in infiltrating effector cells with upregulated immune checkpoint markers within the TME, and increased frequency of specific high-risk genomic alterations. Further assessment in cell line models revealed increased susceptibility to cytotoxic T cells when iron metabolism is elevated, despite upregulation of the checkpoint ligand PD-L1. Conclusions: High TFRC expression, therefore, indicates worse clinical risk across multiple common tumor types but potentially increased susceptibility to cytotoxic immune effectors, informing the development of TFR1 biomarker-driven therapeutic strategies. Full article

Background: Sézary syndrome (SS) is an aggressive leukemic variant of cutaneous T-cell lymphoma (CTCL) with distinct clinical and biological features compared to rarer entities such as primary cutaneous CD8⁺ aggressive epidermotropic cytotoxic T-cell lymphoma (PCAECTCL). Although recurrent genomic alterations in CTCL have been described, comparative analyses at the pathway level across biologically divergent subtypes remain limited. Here, we leveraged a conversational artificial intelligence (AI) platform for precision oncology to enable rapid, integrative, and hypothesis-driven interrogation of publicly available genomic datasets. Methods: We conducted a secondary analysis of somatic mutation and clinical data from the Columbia University CTCL cohort accessed via cBioPortal. Cases were stratified into SS (n = 26) and PCAECTCL (n = 13). High-confidence coding variants were curated and mapped to biologically relevant signaling pathways and functional gene categories implicated in CTCL pathogenesis. Pathway-level mutation frequencies were compared using Fisher’s exact tests, with effect sizes quantified as odds ratios. Tumor mutational burden (TMB) was compared using the Wilcoxon rank-sum test. Subtype-specific co-mutation patterns were evaluated using pairwise association analyses and visualized through oncoplots and network heatmaps. A conversational AI agent, AI-HOPE, was used to iteratively refine cohort definitions, prioritize pathway-level signals, and contextualize findings. Results: TMB was comparable between SS and PCAECTCL (p = 0.96), indicating no significant difference in global mutational load. In contrast, pathway-centric analyses revealed marked qualitative differences. SS demonstrated enrichment of alterations in epigenetic regulators, tumor suppressor and cell-cycle control pathways, NFAT signaling, and DNA damage response mechanisms, consistent with transcriptional dysregulation and immune modulation. PCAECTCL exhibited relatively higher frequencies of alterations involving epigenetic regulators and MAPK pathway signaling, suggesting distinct oncogenic dependencies. Co-mutation analysis revealed a more constrained and focused interaction landscape in SS, whereas PCAECTCL displayed broader and more heterogeneous co-mutation networks, indicative of divergent evolutionary trajectories. Notably, ERBB2 mutations were significantly enriched between subtypes (p = 0.031), highlighting a potential subtype-specific therapeutic vulnerability. Conclusions: This study demonstrates that SS is distinguished from PCAECTCL not by increased mutational burden but by distinct pathway-level architectures, particularly involving epigenetic regulation, immune signaling, and transcriptional control. These findings generate biologically grounded, testable hypotheses for subtype-specific therapeutic targeting and underscore the value of conversational AI as a scalable framework for accelerating discovery in translational cancer genomics. Full article

Background: Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal malignancy. Next-generation sequencing (NGS) enables molecular characterization and may identify clinically actionable alterations; however, real-world multicenter data linking genomic subgroups to survival outcomes remain limited. We aimed to characterize the molecular landscape of NGS-tested PDAC in a Turkish multicenter cohort and evaluate the association of key molecular alterations, including KRAS status and KRAS variant subgroups, with survival outcomes. Methods: We conducted a multicenter retrospective cohort study including patients with pathologically diagnosed PDAC between 2017 and 2025 who underwent tumor-based NGS in routine clinical practice. Overall survival (OS) was calculated from the date of metastasis, defined as the date of diagnosis for de novo metastatic disease and the date of first documented distant recurrence for recurrent cases. Progression-free survival (PFS) was calculated from the initiation of first-line systemic therapy for metastatic disease to progression or death. Survival was estimated using the Kaplan–Meier method and compared using the log-rank test. Multivariable Cox proportional hazards models were constructed for OS and PFS using clinically relevant covariates selected a priori. Results: A total of 98 patients underwent molecular profiling, and survival analyses were performed in 92 patients with available OS/PFS data. KRAS mutations were detected in 83.7% (82/98) of patients, with predominant variants G12D (47.6%), G12V (30.5%), and G12R (12.2%). TP53 mutations were present in 59.2% (58/98) of tumors, and all tumors were microsatellite stable. Tumor mutational burden data were available for 72 patients; the median TMB was 3.83 mutations/Mb, and 15.3% of evaluable tumors had a TMB ≥ 10 mutations/Mb. Excluding KRAS, clinically actionable alterations were identified in 4.1% of patients, whereas an additional 32.7% harbored potentially actionable or investigational alterations. Median OS was 14.0 months (95% CI, 11.7–16.3), and median PFS was 6.0 months (95% CI, 4.3–7.7). In unadjusted analyses, OS and PFS did not differ significantly according to KRAS mutation status (OS, p = 0.967; PFS, p = 0.652), TP53 mutation status (OS, p = 0.404; PFS, p = 0.510), or KRAS variant subgroup (OS, p = 0.332; PFS, p = 0.194). In multivariable Cox analyses, KRAS mutation status was not independently associated with OS (aHR 1.13, 95% CI 0.56–2.28; p = 0.727) or PFS (aHR 1.09, 95% CI 0.59–2.01; p = 0.780), whereas ECOG performance status remained the strongest adverse clinical factor. Conclusions: In this multicenter real-world PDAC cohort, the molecular landscape was dominated by KRAS and TP53 alterations, whereas clinically actionable non-KRAS alterations were identified in only a minority of patients. After adjustment for major clinical covariates, KRAS mutation status was not independently associated with OS or PFS. Molecular profiling may still be useful for identifying uncommon potentially targetable alterations; however, larger clinically annotated multicenter studies are needed to better define its prognostic and treatment-directing value in routine practice. Full article